Users of the World Wide Web are familiar with the various available search engines that can be used for locating content. Search engines are provided by a number of entities and may be stand-alone search engines for performing searches across one or more websites, or embedded in websites for performing a search in content present in the website where the search engine is embedded.
While searching for content, users generally enter a search term to express the intent of their search, for example when they are looking for a specific product on a website, looking for a specific product across multiple websites, and so on. This search term may be a single word, a string of words, and so on.
The search terms play a vital role in providing an intuitive consumer experience. However, different users provide different search terms, and these terms may show a fat-tail distribution, i.e. a probability distribution that has the property that it exhibits large skewness or kurtosis. For example, there may be too many unique search terms provided by different users to achieve the same set of intents for these users where their intents are similar. Thus, it becomes challenging to predict and/or suggest search terms to a user.